sqlalchemy-cubrid

SQLAlchemy 2.0 dialect for the CUBRID database — Python ORM, schema reflection, Alembic migrations, and full type system support.

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Why sqlalchemy-cubrid?

CUBRID is a high-performance open-source relational database, widely adopted in Korean public-sector and enterprise applications. Until now, there was no production-ready SQLAlchemy dialect that supports the modern 2.0 API.

sqlalchemy-cubrid bridges that gap:

• Full SQLAlchemy 2.0 dialect with statement caching and PEP 561 typing
• 426 offline tests with 99%+ code coverage — no database required to run them
• Tested against 4 CUBRID versions (10.2, 11.0, 11.2, 11.4) across Python 3.10 -- 3.13
• CUBRID-specific DML constructs: ON DUPLICATE KEY UPDATE, MERGE, REPLACE INTO
• Alembic migration support out of the box
• Two driver options — C-extension (cubrid://) or pure Python (cubrid+pycubrid://)

Architecture

flowchart TD
    app["Application"] --> sa["SQLAlchemy Core/ORM"]
    sa --> dialect["CubridDialect"]
    dialect --> pycubrid["pycubrid driver"]
    dialect --> cext["CUBRIDdb driver"]
    pycubrid --> server["CUBRID Server"]
    cext --> server

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flowchart TD
    expr["SQL Expression"] --> compiler["CubridSQLCompiler"] --> sql["SQL String"]

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Requirements

• Python 3.10+
• SQLAlchemy 2.0 – 2.1
• CUBRID-Python (C-extension) or pycubrid (pure Python)

Installation

pip install sqlalchemy-cubrid

With the pure Python driver (no C build needed):

pip install "sqlalchemy-cubrid[pycubrid]"

With Alembic support:

pip install "sqlalchemy-cubrid[alembic]"

Quick Start

Core (Connection-Level)

from sqlalchemy import create_engine, text

engine = create_engine("cubrid://dba:password@localhost:33000/demodb")

with engine.connect() as conn:
    result = conn.execute(text("SELECT 1"))
    print(result.scalar())

ORM (Session-Level)

from sqlalchemy import create_engine, String
from sqlalchemy.orm import DeclarativeBase, Mapped, Session, mapped_column


class Base(DeclarativeBase):
    pass


class User(Base):
    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
    name: Mapped[str] = mapped_column(String(100))
    email: Mapped[str] = mapped_column(String(200), unique=True)


engine = create_engine("cubrid://dba:password@localhost:33000/demodb")
Base.metadata.create_all(engine)

with Session(engine) as session:
    user = User(name="Alice", email="alice@example.com")
    session.add(user)
    session.commit()

Features

• Complete type system -- numeric, string, date/time, bit, LOB, and collection types
• SQL compilation -- SELECT, JOIN, CAST, LIMIT/OFFSET, subqueries, CTEs, window functions
• DML extensions -- ON DUPLICATE KEY UPDATE, MERGE, REPLACE INTO, FOR UPDATE, TRUNCATE
• DDL support -- COMMENT, IF NOT EXISTS / IF EXISTS, AUTO_INCREMENT
• Schema reflection -- tables, views, columns, PKs, FKs, indexes, unique constraints, comments
• Alembic migrations via CubridImpl (auto-discovered entry point)
• All 6 CUBRID isolation levels (dual-granularity: class-level + instance-level)

Documentation

Guide	Description
Connection	Connection strings, URL format, driver setup, pool tuning
Type Mapping	Full type mapping, CUBRID-specific types, collection types
DML Extensions	ON DUPLICATE KEY UPDATE, MERGE, REPLACE INTO, query trace
Isolation Levels	All 6 CUBRID isolation levels, configuration
Alembic Migrations	Setup, configuration, limitations, batch workarounds
Feature Support	Comparison with MySQL, PostgreSQL, SQLite
ORM Cookbook	Practical ORM examples, relationships, queries
Development	Dev setup, testing, Docker, coverage, CI/CD
Driver Compatibility	CUBRID-Python driver versions and known issues
Troubleshooting	Common issues, error solutions, debugging techniques

Compatibility

	Python 3.10	Python 3.11	Python 3.12	Python 3.13
Offline Tests	✅	✅	✅	✅
CUBRID 11.4	✅	--	✅	--
CUBRID 11.2	✅	--	✅	--
CUBRID 11.0	✅	--	✅	--
CUBRID 10.2	✅	--	✅	--

FAQ

How do I connect to CUBRID with SQLAlchemy?

from sqlalchemy import create_engine
engine = create_engine("cubrid://dba:password@localhost:33000/demodb")

For the pure Python driver (no C build needed): create_engine("cubrid+pycubrid://dba@localhost:33000/demodb")

Does sqlalchemy-cubrid support SQLAlchemy 2.0?

Yes. sqlalchemy-cubrid is built for SQLAlchemy 2.0+ and supports the new 2.0-style API including Session.execute(), typed Mapped[] columns, and statement caching.

Does sqlalchemy-cubrid support Alembic migrations?

Yes. Install with pip install "sqlalchemy-cubrid[alembic]". The dialect auto-registers via entry point. Note that CUBRID auto-commits DDL, so migrations are not transactional.

What Python versions are supported?

Python 3.10, 3.11, 3.12, and 3.13.

Does CUBRID support RETURNING clauses?

No. CUBRID does not support INSERT ... RETURNING or UPDATE ... RETURNING. Use cursor.lastrowid or SELECT LAST_INSERT_ID() instead.

How do I use ON DUPLICATE KEY UPDATE with CUBRID?

from sqlalchemy_cubrid import insert
stmt = insert(users).values(name="Alice").on_duplicate_key_update(name="Alice Updated")

What's the difference between cubrid:// and cubrid+pycubrid://?

cubrid:// uses the C-extension driver (CUBRIDdb) which requires compilation. cubrid+pycubrid:// uses the pure Python driver which installs with pip alone — no build tools needed.

Related Projects

• pycubrid — Pure Python DB-API 2.0 driver for CUBRID
• cubrid-python-cookbook — Production-ready Python examples for CUBRID

Roadmap

See ROADMAP.md for this project's direction and next milestones.

For the ecosystem-wide view, see the CUBRID Labs Ecosystem Roadmap and Project Board.

Contributing

See CONTRIBUTING.md for guidelines and docs/DEVELOPMENT.md for development setup.

Security

Report vulnerabilities via email -- see SECURITY.md. Do not open public issues for security concerns.

License

MIT -- see LICENSE.